Signal processing based on signal subband typing

Abstract

A frequency modulated continuous wave (FMCW) light detection and ranging (LIDAR) system includes a processor and a memory. The memory stores instructions that, when executed by the processor, cause the system to: generate subbands in a frequency domain based on a range-dependent time domain baseband signal, classify each subband into a subband type, select processing parameters for each subband based on the respective subband type, and process each of the subbands using the selected processing parameters for the subband.

What is claimed is: 
     
       1. A frequency modulated continuous wave (FMCW) light detection and ranging (LIDAR) system, comprising:
 a processor; 
 a memory to store instructions that, when executed by the processor, cause the system to:
 generate subbands in a frequency domain based on a range-dependent time domain baseband signal generated by an optical detector based on a return signal received by the LIDAR system, the return signal comprising a reflection of an optical beam transmitted by the LIDAR system; 
 classify each subband into one of a plurality of subband types; 
 select processing parameters for each subband based on a respective one of the plurality of subband types; and 
 process each of the subbands using the selected processing parameters for the subband for target detection. 
 
 
     
     
       2. The FMCW LIDAR system of  claim 1 , wherein, to generate subbands in the frequency domain, the system is further to:
 perform a discrete Fourier transform (DFT) on the range-dependent time domain baseband signal using a DFT processor. 
 
     
     
       3. The FMCW LIDAR system of  claim 2 , wherein a length of the DFT is based on a range resolution associated with each subband type, and wherein a frequency of the DFT is based on an angular resolution associated with each subband type. 
     
     
       4. The FMCW LIDAR system of  claim 1 , wherein each subband is classified into one of the plurality of subband types based on subband typing criteria, wherein the subband typing criteria for a respective subband are based on one or more of a peak signal energy in the respective subband, an average signal-to-noise ratio in the respective subband, a peak signal-to-noise ratio in the respective subband, a scene characteristic, a target velocity relative to the LIDAR system, an azimuth scan angle, or an elevation scan angle. 
     
     
       5. The FMCW LIDAR system of  claim 1 , wherein a first subband type of the plurality of subband types is based on a comparison of a characteristic of a respective subband of the subbands to a characteristic threshold corresponding to a predefined close-range target, and wherein a second subband type of the plurality of subband types is based on a comparison of the characteristic of the respective subband to a second characteristic threshold corresponding to a predefined long-range target. 
     
     
       6. The FMCW LIDAR system of  claim 5 , wherein the characteristic is one of a frequency of the respective subband, a peak energy of the respective subband, a peak signal-to-noise ratio (SNR) of the respective subband or an average signal-to-noise ratio (SNR) of the respective subband. 
     
     
       7. The FMCW LIDAR system of  claim 1 , wherein, to process each of the subbands using the selected subband processing parameters for the subband, the system is further to:
 filter each of the subbands with a digital filter, wherein a length of the digital filter is based on the subband type of the subband. 
 
     
     
       8. A method in a frequency modulated continuous wave (FMCW) light detection and ranging (LIDAR) system, comprising:
 generating, by a processing device of the LIDAR system, subbands in a frequency domain based on a range-dependent time domain baseband signal generated by an optical detector based on a return signal received by the LIDAR system, the return signal comprising a reflection of an optical beam transmitted by the LIDAR system; 
 classifying each subband into one of a plurality of subband types; 
 selecting processing parameters for each subbandbased on a respective one of the plurality of subband types; and 
 processing each of the subbands using the selected processing parameters for the subband for target detection. 
 
     
     
       9. The method of  claim 8 , wherein, to generate subbands in the frequency domain, the system is further to:
 performing a discrete Fourier transform (DFT) on the range-dependent time domain baseband signal using a DFT processor. 
 
     
     
       10. The method of  claim 9 , wherein a length of the DFT is based on a range resolution associated with each subband type, and wherein a frequency of the DFT is based on an angular resolution associated with each subband type. 
     
     
       11. The method of  claim 8 , wherein each subband is classified into one of the plurality of subband types based on subband typing criteria, wherein the subband typing criteria for a respective subband are based on one or more of a peak signal energy in the respective subband, an average signal-to-noise ratio in the respective subband, a peak signal-to-noise ratio in the respective subband, a scene characteristic, a target velocity relative to the LIDAR system, an azimuth scan angle, or an elevation scan angle. 
     
     
       12. The method of  claim 8 , wherein a first subband type of the plurality of subband types is based on a comparison of a characteristic of a respective subband of the subbands to a characteristic threshold corresponding to a predefined close-range target, and wherein a second subband type of the plurality of subband types is based on a comparison of the characteristic of the respective subband to a second characteristic threshold corresponding to a predefined long-range target. 
     
     
       13. The method of  claim 12 , wherein the characteristic is one of a frequency of the respective subband, a peak energy of the respective subband, a peak signal-to-noise ratio (SNR) of the respective subband or an average signal-to-noise ratio (SNR) of the respective subband. 
     
     
       14. The method of  claim 8 , wherein, to process each of the subbands using the selected subband processing parameters for the subband, the system is further to:
 filtering each of the subbands with a digital filter, wherein a length of the digital filter is based on the subband type of the subband. 
 
     
     
       15. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor in a frequency modulated continuous wave (FMCW) light detection and ranging (LIDAR) system, cause the LIDAR system to:
 generate, by the processor, subbands in a frequency domain based on a range-dependent time domain baseband signal generated by an optical detector based on a return signal received by the LIDAR system, the return signal comprising a reflection of an optical beam transmitted by the LIDAR system; 
 classify each subband into one of a plurality of subband types; 
 select processing parameters for each subbandbased on a respective one of the plurality of subband types; and 
 process each of the subbands using the selected processing parameters for the subband for target detection. 
 
     
     
       16. The non-transitory computer-readable storage medium of  claim 15 , wherein, to generate subbands in the frequency domain, the system is further to:
 perform a discrete Fourier transform (DFT) on the range-dependent time domain baseband signal using a DFT processor. 
 
     
     
       17. The non-transitory computer-readable storage medium of  claim 16 , wherein a length of the DFT is based on a range resolution associated with each subband type, and wherein a frequency of the DFT is based on an angular resolution associated with each subband type. 
     
     
       18. The non-transitory computer-readable storage medium of  claim 15 , wherein each subband is classified into one of the plurality of subband types based on subband typing criteria, wherein the subband typing criteria for a respective subband are based on one or more of a peak signal energy in the respective subband, an average signal-to-noise ratio in the respective subband, a peak signal-to-noise ratio in the respective subband, a scene characteristic, a target velocity relative to the LIDAR system, an azimuth scan angle, or an elevation scan angle. 
     
     
       19. The non-transitory computer-readable storage medium of  claim 15 , wherein a first subband type of the plurality of subband types is based on a comparison of a characteristic of a respective subband of the subbands to a characteristic threshold corresponding to a predefined close-range target, and wherein a second subband type of the plurality of subband types is based on a comparison of the characteristic of the respective subband to a second characteristic threshold corresponding to a predefined long-range target. 
     
     
       20. The non-transitory computer-readable storage medium of  claim 19 , wherein the characteristic is one of a frequency of the respective subband, a peak energy of the respective subband, a peak signal-to-noise ratio (SNR) of the respective subband or an average signal-to-noise ratio (SNR) of the respective subband.